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When I first saw an article entitled Fact-Checking Live News In Just a Few Second, by Laine Higgins in the November 24-25, 2018 print edition of The Wall Street Journal (subscription required online), I though the pagination might be in error. The upper left corner showed the number to be “B4”. I think it would have been more accurate to have number the page “B4 and After” because of the coverage of a remarkable new program being developed called Voyc.

At a time of such heightened passions in domestic US and international news, with endless charges and counter-charges of “fake news” and assertions of “real news”, this technology can assess the audio of live news media broadcasts to determine the veracity of statements made within seconds of being spoken.

Someone please boot up John Lennon’s Gimme Some Truth as he passionately protested the need for truth in the world when it was first released on his classic Imagine album in 1971.¹ This still sounds as timely and relevant today as it did 47 years ago, particularly in this new article that, well, sings the praises of this new fact-checking app.

I suggest naming a new category for these programs and services to be called “fact-check tech”. I think it’s kinds catchy.

Let’s focus the specifics of this remarkable report. I highly recommend reading it in its entirety if you have full WSJ.com access. Below I will summarize and annotate it, and then pose some of my own question-checked questions.

Downstreaming

Image from Pixabay.com

The current process of “fact-checking live news” has been slow. Quite often, by the time a human fact-checker has researched and affirmed a disputed claim, subsequently misleading information based upon it has been distributed and “consumed”.

Voyc has the potential to expedite all this. It is being developed by Sparks Grove, the innovation and experience department of a consultancy called North Highland. Part of the development process involved interviewing a large number of “print and broadcast journalists” from the US, UK and Ireland about how to minimize and push back against misinformation as it affects the news.

The software is built upon artificial intelligence technology. It is capable of identifying a “questionable statement” in as quickly as two seconds. The system transcribes live audio and then runs it through a “database of fact” compiled from “verified government courses” and “accredited fact-checking organizations”. In the process, it can:

highlight statements that conflict as highlighted by its vetting process

send an alert to a news producer identifying the conflict, or

contact someone else who can make further inquiries about the assertion in question

This system was conceived by Jack Stenson, Spark Grove’s innovation lead. He said that within the news media, in an attempt to shorten the connection of “people to information”, Voyc is an effort to connect them “to what might be the most accurate truth”. Voyc’s designers were very cautious to avoid dispositively labeling any misleading statements it finds as being neither “true” nor “false”. Mr. Stenson does not want a result that “shuts down the conversation”, but rather, intends for the system to assist in stimulating “debates”.

Currently, there are other similar initiatives to develop similar technologies. These include,

Full Fact, created by a nonprofit in Britain, is applying both AI and machine learning algorithms to improve its tools that identify the “incidence and source of misinformation on television broadcasts”.

Voyc is distinguished from them insofar as it fact-checks news audio in nearly real-time whereas the others do their checks against existing published sources.

Image from Pixabay.com

Upstreaming

Mr. Stenson foresees applications of Voyc by news producers to motivate “presenters” to explore their story topics with follow-up analyses in the forms of :

one-on-one interviews

panel discussions

debates

This software in still in its prototype stage and there is no target date for its introduction into television production facilities. Its developers are working to improving its accuracy when recording and “transcribing idiosyncratic speech patterns”. These include dialects, as well as “ums” and “ahs” ² when people speak.

According to Lucas Graves, an associate professor at the University of Wisconsin Madison’s School of Journalism and Mass Communication, because of the “nuanced nature” involved in fact-checking (as Voyc is attempting), this process involves both identifying and contextualizing a statement in dispute. This is the critical factor in “verifying claims made on live news”. As broadcasters do not want to appear “partisan” or otherwise making a contemporaneous challenge without all of the facts readily at hand, the real utility of a fact-checking a system will be to challenge a claim in very close proximity to its being spoken and broadcasted.

Looking back in time to dramatize the exciting potential of this forward-looking technology, let’s recall what Edith Anne (played by Lily Tomlin) on Saturday Night Live always said in concluding her appearances when she exclaimed “and that’s the truth“.

“Polygraph”, image by Rodger Bridges

My Questions

What additional features and functionalities should Voyc’s developers consider adding or modifying? What might future releases and upgrades look like?

What data and personal privacy and ethical considerations should Voyc’s designers and programmers take into consideration in their work?

What other market sectors might benefit from fact-check tech such as applying it during expert testimony, education training or government hearings?

Could Voyc be licensed to other developers on a commercial or open source basis?

Can and should Voyc be tweaked to be more industry-specific, knowledge domain-specific or cultural-specific?

1. This was also the opening theme song of the radio show called Idiot’s Delight, hosted for many years by Vin Scelsa who, for nearly five decades, on various commercial, satellite and public stations in New York was a leading figure in rock, progressive and freeform radio.

No, “The Algorithms” was not a stylishly alternative spelling for a rock and roll band once led by the former 45th Vice President of the United States that was originally called The Al Gore Rhythms.

That said, could anything possibly be more quintessentially human than all of the world’s many arts during the past several millennia? From the drawings done by Og the Caveman¹ on the walls of prehistoric caves right up through whatever musician’s album has dropped online today, the unique sparks of creative minds that are transformed into enduring works of music, literature, film and many other media are paramount among the diversity of things that truly set us apart from the rest of life on Earth.

Originality would seem to completely defy being reduced and formatted into an artificial intelligence (AI) algorithm that can produce new artistic works on its own. Surely something as compelling, imaginative and evocative as Springsteen’s [someone who really does have a rock and roll band with his name in it] epic Thunder Road could never have been generated by an app.

Well, “sit tight, take hold”, because the dawn of new music produced by AI might really be upon us. Whether you’ve got a “guitar and learned how to make it talk” or not, something new is emerging out there. Should all artists now take notice of this? Moreover, is this a threat to their livelihood or a new tool to be embraced by both musicians and their audiences alike? Will the traditional battle of the bands be transformed into the battle of AI’s? Before you “hide ‘neath the covers and study your pain” over this development, let’s have a look at what’s going on.

A fascinating and intriguing new report about this entitled A.I. Songwriting Has Arrived. Don’t Panic, by Dan Reilly, was posted on Fortune.com on October 25, 2018. I highly recommend clicking through and reading it if you have an opportunity. I will summarize and annotate it here, and then pose several of my own instrument-al questions.

Treble Clef

Image from Pexels.com

Previously, “music purists” disagreed about whether music tech innovations such as sampling and synthesizers were a form of cheating among recording artists. After all, these have been used in numerous hit tunes during the past several decades.

Now comes a new controversy over whether using artificial intelligence in songwriting will become a form of challenge to genuine creativity. Some current estimates indicate that during the next ten years somewhere between 20 to 30 percent of the Top 40 chart will be in part or in full composed by machine learning systems. The current types of AI-based musical applications include:

Cueing “an array of instrumentation” ranging from orchestral to hip-hop compositions, and

“Level 2” music is “crafted by a machine” but still performed by real musicians

“Level 3” music is both crafted and performed by machines

Drew Silverstein, the CEO of Amper Music, a software company in New York, has developed “AI-based music composition software”. This product enables musicians “to create and download ‘stems'”, the company’s terminology for “unique portions of a track” on a particular instrument and then to and modify them. Silverstein believes that such “predictive tools” are part of an evolving process in original music.²

Other participants in this nascent space of applying algorithms in a variety of new ways to help songwriters and musicians include:

The applications of AI in music are not as entirely new as they might seem. For example, David Bowie helped in creating a program called Verbasizer for the Apple Mac. It was used on his 1995 album entitled Outside to create “randomized portions of his inputted text” to generate original lyrics “with new meanings and moods”. Bowie discussed his usage of the Verbasizer in a 1997 documentary about his own creative processes entitled Inspirations.

Other musicians, including Taryn Southern, who was previously a contestant on American Idol, used software from Amper Music, Watson Beat and other vendors for the eight songs on her debut album, the palindrome-entitled I Am AI, released in 2017. (Here is the YouTube video of the first track entitled Break Free.) She believes that using these tools for songwriting is not depriving anyone of work, but rather, just “making them work differently”.

Taking a different perspective about this is Will.i.am, the music producer, songwriter and member of the Black Eyed Peas. He is skeptical of using AI in music because of his concerns over how this technological assistance “is helping creative songwriters” He also expressed doubts concerning the following issues:

What is AI’s efficacy in the composition process?

How will the resulting music be distributed?

Who is the audience?

How profitable will it be?

He also believes that AI cannot reproduce the natural talents of some of the legendary songwriters and performers he cites, in addition to the complexities of the “recording processes” they applied to achieve their most famous recordings.

For musical talent and their representatives, the critical issue is money including, among other things, “production costs to copyright and royalties”. For instance, Taryn Southern credits herself and Amper with the songwriting for I Am AI. However, using this software enabled her to spend her funding for other costs besides the traditional costs including “human songwriters”, studio musicians, and the use of a recording studio”.

To sum up, at this point in time in the development of music AIs, it is not anticipated that any truly iconic songs or albums will emerge from them. Rather, it is more likely that a musician “with the right chops and ingenuity” might still achieve something meaningful and in less time with the use of AI.

Indeed, depending on the individual circumstances of their usage, these emerging AI and machine learning music systems may well approach industry recognition of being, speaking of iconic albums – – forgive me, Bruce – – born to run.

Image from Pixabay.com

My Questions

Should musicians be ethically and/or legally obligated to notify purchasers of their recordings and concert tickets that an AI has been used to create their music?

Who owns the intellectual property rights of AI-assisted or wholly derived music? Is it the songwriter, music publisher, software vendor, the AI developers, or some other combination therein? Do new forms of contracts or revisions to existing forms of entertainment contracts need to be created to meets such needs? Would the Creative Commons licenses be usable here? How, and to whom, would royalties be paid and at what percentage rates?

Can AI-derived music be freely sampled for incorporation into new musical creations by other artists? What about the rights and limitations of sampling multiple tracks of AI-derived music itself?

How would musicians, IP owners, music publishers and other parties be affected, and what are the implications for the music industry, if developers of a musical AIs make their algorithms available on an open source basis?

What new entrepreneurial and artistic opportunities might arise for developing customized add-ons, plug-ins and extensions to music AIs? How might these impact IP and music industry employment issues?

Is there any product, service or technology out there today that’s just a click away from offering people the virtual equivalent of a cure for the common cold that costs less than a dollar and tastes better than chocolate? No, of course not. But as new innovations inevitably rise and fall along the waves of the tech hype cycle, the true potential of The Next Big Tech Thing often takes years to become fully realized and optimized for a deep and wide variety of markets.

One of today’s leading candidates competing for this top-level billing is the blockchain.¹ It is enjoying massive media buzz, investment and experimentation in configuring it for a diversity of applications including, among many others, food supply chains, financial services and artists rights. This technology is providing new means to accomplish business tasks more securely and reliably, thus increasing operational efficiencies.

Yet whether the blockchain can and will fully and effectively scale in all circumstances still remains to be seen by many sectors of the business world. An inherently key question at the very heart of the blockchain’s growth and acceptance is whether marketers and advertisers can leverage many of its technological virtues and, if so, how they can best accomplish this?

I will summarize and annotate this, reference in some related Subway Fold posts, and then pose some of my own ad-free questions.

The Benefits of Diminishing Transaction Costs

Economic Gardening, Image by Missy Schmidt

According to a February 2018 CMO Survey, just 8% of its participants rated the usage of the blockchain in their marketing operations as being “moderately or very important”. This technology is still “not well understood” among marketers and perceived as being over-hyped. This has resulted in a “wait and see” attitude about it. Nonetheless, there are compelling reasons to understand the blockchain and build specific marketing applications for it that will be more likely to benefit early adopters and innovators.

The blockchain’s virtues of “transparency, immutability and security” make it very suitable for a wide range of transactional and managerial functions. Likewise, it lowers the costs involved in executing all of these activities and, even more importantly, the need to rely so heavily on the web’s giant advertising intermediaries (primarily Google and Facebook), may be reduced. As well, the means now exist using this technology to permit consumers to better “own and control” their personal data.²

Currently, electronic transactions using credit and debit cards involve significant costs to online and real-world vendors. These associated costs are passed along to consumers. Sellers often set minimum purchase thresholds to maintain their profitability.

However, the transactional costs of using the blockchain are approaching zero. For example, MasterCard and Visa have implemented blockchain-based alternative systems enabling customers to “send money in any local currency”, without using a credit card. This again removes any embedded intermediaries and “connects directly to the banks” involved. Consequently, cross-border fees can be dispensed.

There are other advantages emerging for marketers and advertisers involving exchanges of real monetary value with consumers. Rather than these professionals all relying on third-parties such as Facebook for acquiring troves of customer data, they could instead use a system of micropayments³ to directly reward consumers for their personal data. For instance, under this alternative model, a supermarket chain could provide shoppers with a mobile app that pays them to install it, tracks their location, and use it for special deals on merchandise at personalized prices4.

Similarly, marketers could employ the use of smart contracts that vitiate the “need for validation, review, or authentication by intermediaries”. These can be engaged when participants subscribe to an email newsletter or customer rewards program. (More on this below.) The micropayments here are dispensed to consumers whenever they respond to a vendor’s emails or advertisements.

Like Flamingo Synapses, Image by Donal Mountain

Alleviating Google’s and Facebook’s Dominance in Online Advertising

This direct-reward-to-consumers architecture could similarly be deployed for the engagement of website ads. Presently, most users are put off by the current system of intrusive pop-ups and other forms of unavoidable online advertising. A growing Web-wide push back to this has been the use of ad-blocking browser add-ons.5

New alternatives based upon the blockchain can “recapture” some this lost ad revenue by directly compensating online consumers “for their attention”6. This could potentially diminish Google’s and Facebook’s lock on the majority of online ad and data revenues.7 Blockchain options will also enable individuals to “control their own online profiles and social graphs”.8

Taken together, these possibilities might permit companies to:

interact directly with their consumers

bypass patronizing the social media and search giants, and

avoid relentless email solicitations and “follow-me ads”

Furthermore, meaningful cost savings can be directly passed along to consumers by virtue of this voluntarily consumed advertising via these types of blockchain-supported conduits.

Image from Pixabay.com

Shutting Down Online Frauds and Spam

By 2016, $7.6 billion was appropriated by “fraudulent or deceptive activity” and is expected to increase soon to nearly $11 billion. Nonetheless, marketing teams who deploy the blockchain to “track their ads” can:

maintain control over their online activities

be more confident that expenditures are going to “ROI-generating activities”, and

measure the effects of their efforts on a per-user and per-mail scale

Thus, to the benefit of marketers and vendors and to the detriment of bad actors online are the following technological advantages:

Verification: The blockchain can be used to provide verification of “the origin and methodology of marketers”. It can likewise reduce or eliminate large-scale phishing spam through the use of micropayments to the recipients of marketing emails. This will enable “companies to identify consumers” who are genuinely interested in their offerings. Micropayments could then be dispensed in exchange for access to various forms of onscreen content.

Security: Such implementations could also potentially defeat malicious hacks using denial of service attacks (DoS) and could make social media sites more resistant to automated bot accounts. The former are attempts to overwhelm web servers with a flood of traffic and latter are widely used for massive distributions of deceptive information, as well as to illegally appropriate “online advertising from big brands”.

Authenticity: A user’s bonafides is one of the main cornerstones of the blockchain. Turning this into a service, Keybase.io is a company currently working on reducing social media fraud. Their blockchain-enabled app permits individual users to prove they are the “rightful owners” of various social media account. This makes marketing easier to monitor and advertising expenses more supportable.

“Origami Fish – Made by June”, image by Penny

Increasing Revenues from Media Viewership

Original and editorial web content built upon blockchain technology can potentially permit media companies to increase their “quality control and copyright protection”.9 For example, Kodak has developed a new product called KODAKOne, an image rights and distribution platform. It uses the blockchain to record the ownership rights to individual images. Photographers will be awarded greater control over their work than they currently have with how their pictures distribution online. In the future, photographers will automatically be sent payments whenever their content is used. This could probably also be used for video content creators whose work has gone viral.

A company called Coupit also uses blockchain tech to enable marketers to join loyalty and affiliate programs whereby consumers can opt-in and “trade rewards with each other”. As a result, marketers can increase their “visibility and transparency” in order to distinguish inactive from loyal consumers. They can next sharpen their marketing strategies to distribute “targeted offers” to each of these categories.

In those cases where marketers employ a data aggregator or analytics processor, using micropayments will permit companies to circumvent ad-blocking apps10. For consumers, this gives then more fine-point control over their personal data and privacy, and rewards them for their willingness to view advertising that they have chosen.

Taking an alternative approach to content monetization is a new web browser called Brave. In addition to providing many built-in privacy and security features, it contains a blockchain-based feature called Basic Attention Tokens (BATs). These enable “publishers to monetize value added services” whereby users can dispense these tokens to sites they choose for content they select.

“The Crystal Ball”, Image by Gyorgy Soponyai

Companies and Consumers are Both Beneficiaries

Along with the progression of the blockchain’s reach and capabilities, business “intermediaries will need to adapt” accordingly. As discussed above, consumers will be exercising increased control and discretion over how they decide to engage with advertisers and Web threats such as spam and phishing will become self-limiting as their current tactics will be economically undermined.

Balancing this power and attention shift, companies might be able to exert greater control over the “quality of inbound traffic” to their marketing programs and achieve greater understanding of their customers’ needs and motivations. When pursuing such “high value customers”, these economic incentives will perhaps result in a correspondingly increase in value.

Given all of these advantages that marketers and advertisers have to gain from further embracing blockchain technology, “finding ways to design and implement” them should be a joint effort among corporate decision-makers not just in marketing but also from the strategy, finance and technology departments. Moreover, innovative applications of the blockchain may ultimately be more beneficially in connecting marketers and advertisers with their intended audiences in ways that may have not been otherwise previously possible.

My Questions

Given that Google and Facebook currently have an overwhelming lock on online advertising’s multi-$billion revenue streams, will they meet any potential challenges to this with their own blockchain-founded variants? If so, how might they be different in their approach to benefit both advertisers and consumers? At the very least, do they even perceive this as a legitimate threat to their business models?

In addition to rewarding consumers with micropayments for ad clicks and content views, what, if anything, could companies do to correspondingly build incentives into their pricing structures for consumers’ purchasers? How should pricing be affected for repeat or bulk purchases by consumers? What if consumers make referrals of additional interested consumers to these blockchain-based vendors?

Would using mixed media such as augmented reality and virtual reality lend themselves to blockchain-based marketing implementations to further attract new potential consumers? That is, in return for micropayments disbursed to capture users’ attention, might enhanced advertising or content consumption experiences benefit both advertisers and consumers who would both end up feeling as though they are receiving added value for their participation?

What new entrepreneurial opportunities for goods, services and technologies might arise from these new and extensible blockchain-based marketing capabilities?

2. X-ref to the concluding paragraph of the June 7, 2018 Subway Fold post entitled Single File, Everyone: The Advent of the Universal Digital Profile, concerning another innovative effort to return full control of personal data to consumers called the Hub of All Things. Two other similar startups that have emerged during the past few weeks are Inrupt and Helm. This is starting to become a very interesting and innovative space. Furthermore, there was a fascinating and far-ranging article in The New York Times on October 19, 2018, entitled How the Blockchain Could Break Big Tech’s Hold on A.I., by Nathaniel Popper, exploring the possibility of using the blockchain as a means for individuals to control and distribute some of their personal information to be used in AI databases.

3. Virtual reality pioneer, Microsoft scientist and author Jaron Lanier presented a persuasive case for this, among many other thought-provoking insights about the digital world, in his book entitled Who Owns the Future? (Simon & Schuster, 2013). Highly recommended reading if you have an opportunity.

Despite the unsettling effects of figuring out fractions, performing long division and taking the square roots of numbers have had for an eternity upon many students in the middle grades, some of these people continue on to adulthood with at least an appreciation of what mathematics can do in the real world. While they might still break into a slight sweat if challenged to quickly calculate the equivalent of 3/8, they still realize the importance of doing so and, moreover, applying that value to solve a problem.

So too, just as math teachers everywhere exhort their students to “put on their thinking caps”, sometimes a math story appears in the news that takes a bit more concentration to fully comprehend, but nonetheless really does have a certain technological cool and practicality to it. What is equally intriguing is when such a new development has the potential to eventually impact other areas of innovation that appear at first to be disparate or even unrecognizable. On its face, scientific advance X could not possibly be related to mathematical outcome Y until, by virtue of some very unconventional thinkers in another field, the real possibility emerges of a workable application of X to achieve Y.

Let’s take our virtual calculators out of their pocket protectors and have a look at such a recent advancement that is not only useful as party fun for math geeks. Rather, it may have meaningful significant in encryption science and, in turn, online security, e-commerce and data privacy. This achievement was reported in a fascinating article entitled Researchers Discover a Pattern to the Seemingly Random Distribution of Prime Numbers, by Liv Boeree, posted on Motherboard.com on September 14, 2018.

I will summarize and annotate this, and then pose several of my own equation-free questions.

Prime Time

Image from Pixabay.com

First, the basics: Prime numbers (“primes”) are whole numbers that are only divisible by 1 and themselves. They start out small as 2, 3 and 5 and range upwards towards infinity.¹ As these primes are plotted out along on a graph they appear to be increasingly random with no discernible or predictable pattern.

Nonetheless, one of the greatest unsolved math problems is called the Reimann Hypothesis which, among its other brain-bending complexities, posits that there may well be a pattern to the distribution of primes but it has not yet been derived.² Discovering such a pattern would be a monumental accomplishment with major significance in mathematics, physics and modern cryptography, the latter of which is based upon large prime numbers. (More about this below).

The unpredictability of finding new primes is not always necessarily a detriment. For example, modern cryptography methods such as the RSA encryption algorithm depends upon this factor when it comes to very large primes. This relies upon the principle that it is simple enough to take two large prime numbers and multiply them but intensely difficult to reverse this in an effort to determine exactly which two primes were used.

In a process known as X-ray diffraction, chemists and physicists study the atomic structure of a material by exposing it to x-rays and observing how the beams “scatter off the atoms within it”. Different materials will produce a variety of such patterns and indicate “how symmetrically their atoms are arranged”. In the case of a crystal, whose atomic structure is more firm than other materials such as liquids, the x-ray’s pattern of diffraction is “more orderly”.

In 2017, the lead author of the paper, Professor Salvatore Torquato, wondered whether primes could be “modeled as atom-like particles” and whether they would also form a pattern. Along with his co-authors, together they “computationally represented the primes as a one-dimensional string of atoms” and then “scattered light off them”.

They found that this created a “quasicrystal-like inference pattern” that was also a previously unseen form of fractal pattern termed “hyperuniformity“. It is exhibited by only a several “materials and systems in nature”. Included among them are prime numbers. This finding might turn out to be useful in studying such non-repeating patterns in a new field of research called “aperiodic order“.

Professor Torquato said in an article in Quanta Magazine entitled A Chemist Shines Light on a Surprising Prime Number Pattern, by Natalie Wolchover, dated May 14, 2018, that there is a resulting implication that primes “are a completely new category of structures” when viewing them as a form of physical system.

Much of the interest surrounding the new paper is its “unique intersection between the physical and more abstract mathematical realms”. As well, it contains a new algorithm that permits the prediction of primes “with high accuracy”. In time this may prove to be another advance in decisively solving the mysteries of the primes.

Image from Pixabay.com (2)

My Questions

If Professor Torquato’s and his co-authors’ paper and algorithm prove to be genuinely able to predict the patterns of the appearance of primes, does this actually strengthen and/or weaken the foundation of RSA-based encryption?

Moreover, if Sir Atiyah’s has, in fact, solved the Reimann Hypothesis, what are the potential positive and negative effects upon the whole field of cryptography? Are there any additional impacts on other fields of science, math, physics and technology?

If and when practical quantum computing becomes a reality and results in the capability to much more rapidly factor primes used in encryption, how will the work of Professor Torquato and Sir Atiyah be affected?

So, how much is 3/8 anyway?

January 11. 2019 Update: It was announced today that Sir Michael Atiyah, mentioned above, has passed away. His obituary on QuantaMagazine.org is entitled Michael Atiyah’s Imaginative State of Mind. Condolences to his family, friends and colleagues.

2. For an outstanding history of the pursuit of prime numbers and the mathematical quest to discover a pattern in their distribution, I very high recommend reading The Music of the Primes: Searching to Solve the Greatest Mystery in Mathematics, by Marcus du Sautoy, Harper Perennial; Reprint edition (August 14, 2012). This is a very accessible and literate book that presents a variety of engaging stories and deep insights into what might otherwise have otherwise appeared to have been a rather dry subject.

There is an age-old expression among New Yorkers that their city will really be a great place one day if someone ever finishes building it. I have heard this many times during my life as a native and lifelong resident of this remarkable place.

Public and private construction goes on each day on a vast scale throughout the five boroughs of NYC. Over the past several decades under successive political administrations, many areas have been re-zoned to facilitate and accelerate this never-ending buildup and built-out. This relentless activity produces many economic benefits for the municipal economy. However, it also results in other detrimental effects including housing prices and rents that continue to soar upward, disruptive levels of noise and waste materials affecting people living nearby, increased stresses upon local infrastructure, and just as regrettably, steady erosion of the unique characters and spirits of many neighborhoods.¹

I will also summarize and annotate this report, and then pose some of my own code compliant questions.

Home on the [Data] Range

Construction on Lexington Avenue, Image by Jeffrey Zeldman

As the ubiquitous pounding of steel and pouring of concrete proceeds unabated, there is truly little or no getting around it. The Map is one component of a $60 million digital initiative established in 2015 which is intended to produce an “impressive level of detail” on much of this cityscape altering activity.

The recent inception of The Map provides everyone in the metro area an online platform to track some of the key details of the largest of these projects plotted across a series of key metrics. An accompanying grid of tables below it lists and ordinates the largest projects based upon these dimensions.

The Map’s user interface presents this “overview of the frenzy of construction” dispersed across the city’s communities using the following configurations:

Each project’s location represented by a blue dot that can be clicked to reveal the property’s contractor, history and any violations.

Cumulative real-time totals of square footage under construction, permits and dwelling units involved. This data can be further filtered by borough.

As well, it provides residents a virtual means to identify who is making all of that real-world blaring construction noise in their neighborhood.²

If I Had a Hammer

Executives, organizations and community advocates representing a diversity of interests have expressed their initial support for The Map.

Second Avenue Subway Update, Image by MTA (2)

The NYC Building Commissioner, Rick D. Chandler, believes this new resource is a means to provide transparency to his department’s tremendous quantity of construction data. Prior to the rollout of The Map, accessing and processing this information required much greater technical and professional skills. Furthermore, the data will be put to use to “improve and streamline the department’s operations”.

According to Andrew Berman, the Executive Director of the non-profit advocacy group Greenwich Village Society for Historic Preservation, he finds The Map to be both useful and “long overdue”. It is providing his group with a more convenient means to discover additional information about the proliferation of project sites in the Village. He also noted that under the previously existing municipal databases, this data was far more challenging to extract. Nonetheless, the new map remains insufficient for him and “other measures were needed” for the city government to increase oversight and enforcement of construction regulations concerning safety and the types of projects are permitted on specific properties.

Local real estate industry trade groups such as the Real Estate Board of New York, are also sanguine about this form of digital innovation, particularly for it accessibility. The group’s current president, John H. Banks, finds that it is “more responsive to the needs of the private sector”, raises transparency and the public’s “awareness of economic activity, jobs and tax revenues” flowing from the city’s construction projects.

Plans are in place to expand The Map based upon user feedback. As well, it will receive daily updates thus providing “a real-time advantage over analyst and industry reports”.

Image from Pixabay.com

My Questions

Does a roadmap currently exist for the projected development path of The Map’s content and functionality? If so, how can all interested parties provide ongoing commentary and support for it?

Are there other NYC databases and data sources that could possibly be integrated into the map? For example, tax, environmental and regulatory information might be helpful.

Can other cities benefit from the design and functionality of The Map to create or upgrade their own versions of similar website initiatives?

What new entrepreneurial, academic and governmental opportunities might now present themselves because of The Map?

1. For a deeply insightful analysis and passionate critique of the pervasive and permanent changes to many of New York’s neighborhoods due to a confluence of political, economic and social forces and interests, I highly recommend reading Vanishing New York: How a Great City Lost Its Soul, by Jeremiah Moss, (Dey Street Books, 2017). While I did not agree with some aspects of his book, the author has expertly captured and scrutinized how, where and why this great city has been changed forever in many ways. (See also the author’s blog Jeremiah’s Vanishing New York for his continuing commentary and perspectives.)

2. Once I lived in a building that had been mercifully quiet for a long time until the adjacent building was purchased, gutted and totally renovated. For four months during this process, the daily noise level by comparison made a typical AC/DC concert sound like pin drop.

Have you ever been employed in a genuinely cooperative and productive environment where you looked forward each day to making your contribution to the enterprise and assisting your colleagues? Conversely, have you ever worked in a highly stressful and unsupportive atmosphere where you dreading going back there nearly every day? Or perhaps you have found in your career that your jobs and employers were somewhere in the mid-range of this spectrum of office cultures.

For all of these good, bad or indifferent workplaces, a key question is whether any of the actions of management to engage the staff and listen to their concerns ever resulted in improved working conditions and higher levels of job satisfaction?

The answer is most often “yes”. Just having a say in, and some sense of control over, our jobs and workflows can indeed have a demonstrable impact on morale, camaraderie and the bottom line. As posited in the Hawthorne Effect, also termed the “Observer Effect”, this was first discovered during studies in the 1920’s and 1930’s when the management of a factory made improvements to the lighting and work schedules. In turn, worker satisfaction and productivity temporarily increased. This was not so much because there was more light, but rather, that the workers sensed that management was paying attention to, and then acting upon, their concerns. The workers perceived they were no longer just cogs in a machine.

Perhaps, too, the Hawthorne Effect is in some ways the workplace equivalent of the Heisenberg’s Uncertainty Principle in physics. To vastly oversimplify this slippery concept, the mere act of observing a subatomic particle can change its position.¹

Giving the processes of observation, analysis and change at the enterprise level a modern (but non-quantum) spin, is a fascinating new article in the September 2018 issue of The Atlantic entitled What Your Boss Could Learn by Reading the Whole Company’s Emails, by Frank Partnoy. I highly recommend a click-through and full read if you have an opportunity. I will summarize and annotate it, and then, considering my own thorough lack of understanding of the basics of y=f(x), pose some of my own physics-free questions.

“Engagement” of Enron’s Emails

By Enron [Public domain], via Wikimedia Commons

Andrew Fastow was the Chief Financial Officer of Enron when the company infamously collapsed into bankruptcy in December 2001. Criminal charges were brought against some of the corporate officers, including Fastow, who went to prison for six years as a result.

After he had served his sentence he became a public speaker about his experience. At one of his presentations in Amsterdam in 2016, two men from the audience approached him. They were from KeenCorp, whose business is data analytics. Specifically, their clients hire them to analyze the email “word patterns and their context” of their employees. This is done in an effort to quantify and measure the degree of the staff’s “engagement”. The resulting numerical rating is higher when they feel more “positive and engaged”, while lower when they are unhappier and less “engaged”.

The KeenCorp representatives explained to Fastow that they had applied their software to the email archives of 150 Enron executives in an effort to determine “how key moments in the company’s tumultuous collapse” would be assessed and a rated by their software. (See also the February 26, 2016 Subway Fold post entitled The Predictive Benefits of Analyzing Employees’ Communications Networks, covering, among other things, a similar analysis of Enron’s emails.)

KeenCorp’s software found the lowest engagement score when Enron filed for bankruptcy. However, the index also took a steep dive two years earlier. This was puzzling since the news about the Enron scandal was not yet public. So, they asked Fastow if he could recall “anything unusual happening at Enron on June 28, 1999”.

Sentimental Journal

Milky Way in Mauritius, Image by Jarkko J

Today the text analytics business, like the work done by KeenCorp, is thriving. It has been long-established as the processing behind email spam filters. Now it is finding other applications including monitoring corporate reputations on social media and other sites.²

The finance industry is another growth sector, as investment banks and hedge funds scan a wide variety of information sources to locate “slight changes in language” that may point towards pending increases or decreases in share prices. Financial research providers are using artificial intelligence to mine “insights” from their own selections of news and analytical sources.

But is this technology effective?

In a paper entitled Lazy Prices, by Lauren Cohen (Harvard Business School and NBER), Christopher Malloy (Harvard Business School and NBER), and Quoc Nguyen (University of Illinois at Chicago), in a draft dated February 22, 2018, these researchers found that the share price of company, in this case NetApp in their 2010 annual report, measurably went down after the firm “subtly changes” its reporting “descriptions of certain risks”. Algorithms can detect such changes more quickly and effectively than humans. The company subsequently clarified in its 2011 annual report their “failure to comply” with reporting requirements in 2010. A highly skilled stock analyst “might have missed that phrase”, but once again its was captured by “researcher’s algorithms”.

In the hands of a “skeptical investor”, this information might well have resulted in them questioning the differences in the 2010 and 2011 annual reports and, in turn, saved him or her a great deal of money. This detection was an early signal of a looming decline in NetApp’s stock. Half a year after the 2011 report’s publication, it was reported that the Syrian government has bought the company and “used that equipment to spy on its citizen”, causing further declines.

Now text analytics is being deployed at a new target: The composition of employees’ communications. Although it has been found that workers have no expectations of privacy in their workplaces, some companies remain reluctant to do so because of privacy concerns. Thus, companies are finding it more challenging to resist the “urge to mine employee information”, especially as text analysis systems continue to improve.

Among the evolving enterprise applications are the human resources departments in assessing overall employee morale. For example, Vibe is such an app that scans through communications on Slack, a widely used enterprise platform. Vibe’s algorithm, in real-time reporting, measures the positive and negative emotions of a work team.

Finding Context

“Microscope”, image by Ryan Adams

Returning to KeenCorp, can their product actually detect any wrongdoing by applying text analysis? While they did not initially see it, the company’s system had identified a significant “inflection point” in Enron’s history on the June 28, 1999 date in question. Fastow said that was the day the board had discussed a plan called “LJM”, involving a group of questionable transactions that would mask the company’s badly under-performing assets while improving its financials. Eventually, LJM added to Enron’s demise. At that time, however, Fastow said that everyone at the company, including employees and board members, was reluctant to challenge this dubious plan.

KeenCorp currently has 15 employees and six key clients. Fastow is also one of their consultants and advisors. He also invested in the company when he saw their algorithm highlight Enron’s employees’ concerns about the LJM plan. He hopes to raise potential clients’ awareness of this product to help them avoid similar situations.

The company includes heat maps as part of its tool set to generate real-time visualizations of employee engagement. These can assist companies in “identifying problems in the workplace”. In effect, it generates a warning (maybe a warming, too), that may help to identify significant concerns. As well, it can assist companies with compliance of government rules and regulations. Yet the system “is only as good as the people using it”, and someone must step forward and take action when the heat map highlights an emerging problem.

Analyzing employees’ communications also presents the need for applying a cost/benefit analysis of privacy considerations. In certain industries such as finance, employees are well aware that their communications are being monitored and analyzed, while in other businesses this can be seen “as intrusive if not downright Big Brotherly”. Moreover, managers “have the most to fear” from text analysis systems. For instance, it can be used to assess sentiment when someone new is hired or given a promotion. Thus, companies will need to find a balance between the uses of this data and the inherent privacy concerns about its collection.

In addressing privacy concerns about data collection, KeenCorp does not “collect, store on report” info about individual employees. All individually identifying personal info is scrubbed away.

Text analysis is still in its early stages. There is no certainty yet that it may not register a false positive reading and that it will capture all emerging potential threats. Nonetheless it is expected to continue to expand and find new fields for application. Experts predict that among these new areas will be corporate legal, compliance and regulatory operations. Other possibilities include protecting against possible liabilities for “allegations of visa, fraud and harassment”.

The key takeaway from the current state of this technology is to ascertain the truth about employees’ sentiments not by snooping, but rather, “by examining how they are saying it”.

My Questions

“Message In a Bottle”, Image from Pixabay.com

Should text analysis data be factored into annual reviews of officers and/or board members? If so, how can this be done and what relative weight should it be given?

Should employees at any or all levels and departments be given access to text analysis data? How might this potentially impact their work satisfaction and productivity?

Is there a direct, casual or insignificant relationship between employee sentiment data and up and/or down movements in market value? If so, how can companies elevate text analysis systems to higher uses?

How can text analysis be used for executive training and development? Might it also add a new dimension to case studies in business schools?

What does this data look like in either or both of short-term and long-term time series visualizations? Are there any additional insights to be gained by processing the heat maps into animations to show how their shape and momentum are changing over time?

Every so often, an ad campaign comes along that is strikingly brilliant for its originality, execution, persuasiveness, longevity, humor and pathos. During the mid-1980’s, one of these bright shining examples was the television ads for Bartles & Jaymes Wine Coolers. They consisted of two fictional characters: Frank Bartles, who owned a winery and did all of the talking, and Ed Jaymes, a farmer who never spoke a word but whose deadpan looks were priceless. They traveled across the US to different locations in pursuit of sales, trying to somehow adapt their approaches to reflect the local surroundings. Bartles was very sincere but often a bit naive in his pitches along the way, best exemplified in this ad and another one when they visited New York.

These commercials succeeded beyond all expectations in simultaneously establishing brand awareness, boosting sales and being laugh-out-loud hilarious because Bartles’s and Jaymes’s were such charming, aw-shucks amateurs. In actuality, these ads were deftly conceived and staged by some smart and savvy creatives from the Hal Riney & Partners agency. For further lasting effect, they always had Bartles express his appreciation to the viewers at the end of each spot with his memorable trademark tagline of “Thanks for your support”. These 30-second video gems are as entertaining today as they were thirty years ago.

But those halcyon days of advertising are long gone. The industry’s primary media back then was limited to print, television and radio. Creativity was its cornerstone and the words “data analytics” must have sounded like something actuaries did in a darkened room while contemplating the infinite. (Who knows, maybe it still does to some degree.)

Fast forwarding to 2018, advertising is an utterly different and hyper-competitive sector whose work product is largely splayed across countless mobile and stationary screens on Planet Earth. Expertly chronicling and precisely assaying the transformative changes happening to this sector is an informative and engaging new book entitled Frenemies: The Epic Disruption of the Ad Business (and Everything Else) [Penguin Press, 2018], by the renowned business author Ken Auletta. Just as a leading ad agency in its day cleverly and convincingly took TV viewers on an endearing cultural tour of the US as we followed the many ad-ventures of Bartles & Jaymes, so too, this book takes its readers on a far-ranging and immersive tour of the current participants, trends, challenges and technologies affecting the ad industry.

A Frenemy of My Frenemy is My Frenemy

Image from Pixabay

This highly specialized world is under assault from a confluence of competitive, online, economic, social and mathematical forces. Many people who work in it are deeply and rightfully concerned about its future and the tenure of their places in it. Auletta comprehensively reports on and assesses these profound changes from deep within the operations of several key constituencies (the “frenemies”, conflating “friend” and “enemy”). At first this might seem a bit too much of “inside baseball” (although the ad pitch remains alive and well), but he quickly and efficiently establishes who’s who and what’s what in today’s morphing ad markets, making this book valuable and accessible to readers both within and outside of this field. It can also be viewed as a multi-dimensional case study of an industry right now being, in the truest sense of the word, disrupted.¹ There is likewise much to learned and considered here by other businesses being buffeted by similar winds.

Frenemies, as thoroughly explored throughout this book, are both business competitors and partners at the same time. They are former and current allies in commerce who concurrently cooperate and compete. Today they are actively infiltrating each other’s markets. The full matrix of frenemies and their threats and relationships to each other includes the interests and perspectives of ad agencies and their clients, social media networks, fierce competition from streamers and original content producers like Netflix², traditional media in transition to digital platforms, consulting companies and, yes, consumers.

Auletta travels several parallel tracks in his reporting. First, he examines the past, present on onrushing future with respect to revenue streams, profits, client bases served, artificial intelligence (AI) driven automation, and the frenemies’ very fluid alliances. Second, he skillfully deploys the investigative journalistic strategy of “following the money” as it ebbs and flows in many directions among the key players. Third, he illuminates the industry’s evolution from Don Draper’s traditional “Mad Men” to 2018’s “math men” who are the data wranglers, analysts and strategists driven by ever more thin-sliced troves of consumer data the agencies and their corporate clients are using to achieve greater accuracy and efficiency in selling their goods and services.

A deep and wide roster of C-level executives from these various groups were interviewed for the book. Chief among them are two ad industry legends who serve as the x and y axes upon which Auletta has plotted a portion of his reporting. One is Martin Sorrell, who was the founder and CEO of WPP, the world’s largest advertising holding company.³ The other is Michael Kassan, the founder and CEO of MediaLink, a multifaceted firm that connects, negotiates and advises on behalf of a multitude of various parties, often competitors in critical matters affecting the ad business. Both of these individuals have significantly shaped modern advertising over many decades and are currently propagating some of the changes spotlighted in the book in trying to keep it vital, relevant and profitable.

Online Privacy v. Online Primacy

“Tug of War”, image by Pixabay

The established tradition of creativity being the primary driver of advertising creation and campaigns has given way to algorithm-driven data analytics. All of the frenemies and a myriad of other sites in many other parsecs of the websphere vacuum up vast amounts of data on users, their online usage patterns, and even go so far as to try to infer their behavioral attributes. This is often combined with additional personal information from third-party sources and data brokers. Armed with all of this data and ever more sophisticated means for sifting and intuiting it, including AI4, the frenemies are devising their campaigns to far more precisely target potential consumers and their cohorts with finely grained customized ads.

The high point of this book is Auletta’s nuanced coverage of the ongoing controversy involving the tension between frenemies using data analytics to increase click-through rates and, hopefully, sales versus respecting the data privacy of people as they traverse the Web. In response to this voracious data collection, millions of users have resisted this intrusiveness by adding free browser extensions such as AdBlock Plus to circumvent online tracking and ad distribution.5 This struggle has produced a slippery slope between the commercial interests of the frenemies and consumers’ natural distaste for advertising, as well as their resentment at having their data co-opted, appropriated and misused without their knowledge or consent. Recently, public and governmental concerns were dramatically displayed in the harsh light of the scandals involving Facebook and Cambridge Analytica.

Furthermore, Google and Facebook dominate the vast majority of online advertising traffic, revenues and, most importantly, the vast quantum of user information which ad agencies believe would be particularly helpful to them in profiling and reaching consumers. Nonetheless, they maintain it is highly proprietary to them alone and much of it has not been shared. Frenemies much?

Additional troubling trends for the ad industry are likewise given a thorough 3-D treatment. Auletta returns to the axiom several times that audiences do not want to be interrupted with ads (particularly on their mobile devices). Look no further than the likes of premium and the major streaming services who offer all of their content uninterrupted in its entirety. The growing ranks of content creators they engage know this and prefer it because they can concentrate on their presentations without commercial breaks slicing and dicing their narrative continuity. The still profitable revenue streams flowing from this are based upon the strengths of the subscription model.

Indeed, in certain cases advertising is being simultaneously disrupted and innovated. Some of the main pillars of the media like The New York Times are now expanding their in-house advertising staff and service offerings. They can offer a diversified array of ads and analyses directly to their advertisers. Likewise, engineering-driven operations like Google and Facebook can deploy their talent benches to better target consumers for their advertisers by extracting and applying insights from their massive databases. Why should their clients continue go to the agencies when their ads can be composed and tracked for them directly?

Adapt or Go Home

“Out with the Old, In with the New”, image by Mark

The author presents a balanced although not entirely sanguine view of the ad industry’s changes to maintain its composure and clients in the midst of this storm. The frenemy camps must be willing to make needed and often difficult adjustments to accommodate emerging technological and strategic survival methods. He examines the results of two contemporary approaches to avoiding adblocking apps and more fully engaging very specific audiences. One is called “native advertising“, which involves advertisers producing commercial content and paying for its placement online or in print to promote their own products. Generally, these are formatted and integrated to appear as though they are integrated with a site’s or publication’s regular editorial content but contain a notice that it is, in fact “Advertising”.

However, Auletta believes that the second adaptive mechanism, the online subscription model, will not be much more sustainable beyond its current successes. Consumers are already spending money on their favorite paywalled sites. But it would seem logical that users might not be thus willing to pay for Facebook and others that have always been free. As well, cable’s cord-cutters are continuing to exhibit steady growing in their numbers and their migrations towards streaming services such as Amazon Prime.6

Among the media giants, CBS seems to be getting their adaptive strategies right from continuing to grow multiple revenue streams. They now have the legal rights and financial resources to produce and sell original programming. They have also recently launched original web programming such as Star Trek: Discovery on a commercial-free subscription basis on CBS All Access. This can readily be seen as a challenge to Netflix despite the fact that CBS also providing content to Netflix. Will other networks emulate this lucrative and eyeball attracting model?

As Auletta also concludes, for now at least, consumers as frenemies, appear to be the beneficiaries of all this tumult. They have many device agnostic platforms, pricing options and a surfeit of content from which to choose. They can also meaningfully reduce, although not entirely eliminate, ads following them all over the web and those pesky stealth tracking systems. Whether they collectively can maintain their advantage is subject to sudden change in this environment.

Because of the timing of the book’s completion and publication, the author and publisher should consider including in any subsequent edition the follow-up impacts of Sorrell’s departure from WPP and his new venture (S4 Capital), the effects of the May 2018 implementation of EU’s General Data Protection Regulation (GDPR), and the progress of any industry or government regulation following the raft of recent massive data breaches and misuses.

Notwithstanding that, however, “Frenemies” fully delivers on all of its book jacket’s promises and premises. It is a clear and convincing case of truth in, well, advertising.

So, how would Frank Bartles and Ed Jaymes 2.0 perceive their promotional travels throughout today’s world? Would their folksy personas play well enough on YouTube to support a dedicated channel for them? Would their stops along the way be Instagram-able events? What would be their reactions when asked to Google something or download a podcast?

Alternatively, could they possibly have been proto-social media influencers who just showed up decades too soon? Nah, not really. Even in today’s digital everything world, Frank and Ed 1.0 still abide. Frank may have also unknowingly planted a potential meme among today’s frenemies with his persistent proclamations of “Thanks for your support”: The 2018 upgrade might well be “Thanks for your support and all of your data”.

September 4, 2018 Update: Today’s edition of The New York Times contains an highly enlightening article directly on point with many of the key themes of Frenemies entitled Amazon Sets Its Sights on the $88 Billion Online Ad Market, by Julie Creswell. The report details Amazon’s significant move into online advertising supported by its massive economic, data analytics, scaling and strategic resources. It comprehensively analyzes the current status and future prospects of the company’s move into direct competition with Google and Facebook in this immense parsec of e-commerce. I highly recommend a click-through and full read of this if you have an opportunity.

1. The classic work on the causes and effect of market disruptions, the disruptors and those left behind is The Innovator’s Dilemma, by Clayton Christensen (HarperBusiness, 2011). The first edition of the book was published in 1992.